import logging
from stdatamodels.jwst import datamodels
from jwst.rscd import rscd_sub
from jwst.stpipe import Step
__all__ = ["RscdStep"]
log = logging.getLogger(__name__)
[docs]
class RscdStep(Step):
"""
Flag the first N groups of MIRI data to 'DO_NOT_USE' in the 2nd and later integrations.
The number of groups, N, for which to
set the GROUPDQ flag to 'DO_NOT_USE' is read in from the RSCD reference file. This number
depends on the readout model and subarray size. The step checks that the total number of groups
in an integration is greater than N+3 before flagging the GROUPDQ array. If the number of groups
is less than N+3 then no flagging is performed, because doing so would leave too few groups
to work with in later steps.
"""
class_alias = "rscd"
spec = """
""" # noqa: E501
reference_file_types = ["rscd"]
[docs]
def process(self, step_input):
"""
Flag the initial groups to 'DO_NOT_USE' in the 2nd and later integrations.
The number of initial groups to flag is read in from the RSCD reference file. This number
varies based on readout mode and subarray size.
Parameters
----------
step_input : `~stdatamodels.jwst.datamodels.RampModel`
Ramp datamodel to be corrected, or the path to the ramp file.
Returns
-------
result : `~stdatamodels.jwst.datamodels.RampModel`
Ramp datamodel with initial groups in an integration flagged as DO_NOT_USE.
Flags are only set of integration 2 and higher.
"""
# Open the input data model
result = self.prepare_output(step_input, open_as_type=datamodels.RampModel)
# check the data is MIRI data
detector = result.meta.instrument.detector
if not detector.startswith("MIR"):
log.warning("RSCD correction is only for MIRI data")
log.warning("RSCD step will be skipped")
result.meta.cal_step.rscd = "SKIPPED"
return result
# Get the name of the rscd reference file to use
rscd_name = self.get_reference_file(result, "rscd")
log.info("Using RSCD reference file %s", rscd_name)
# Check for a valid reference file
if rscd_name == "N/A":
log.warning("No RSCD reference file found")
log.warning("RSCD step will be skipped")
result.meta.cal_step.rscd = "SKIPPED"
return result
# Load the rscd ref file data model
rscd_model = datamodels.RSCDModel(rscd_name)
# Do the rscd correction
result = rscd_sub.do_correction(result, rscd_model)
# Cleanup
del rscd_model
return result